(* Content-type: application/mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy='Mathematica 6.0' *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[       145,          7]
NotebookDataLength[    294153,       5555]
NotebookOptionsPosition[    290829,       5445]
NotebookOutlinePosition[    291165,       5460]
CellTagsIndexPosition[    291122,       5457]
WindowFrame->Normal
ContainsDynamic->False*)

(* Beginning of Notebook Content *)
Notebook[{

Cell[CellGroupData[{
Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "[", 
   RowBox[{
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{"2", "*", 
        RowBox[{"a", "/", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"2", "*", 
            RowBox[{"b", "^", "2"}], "*", 
            RowBox[{"a", "^", "2"}]}], "+", "  ", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1", "-", " ", 
               RowBox[{
                RowBox[{"b", "^", "2"}], "*", 
                RowBox[{"a", "^", "2"}]}]}], ")"}], "/", "2"}], "*", "x"}]}], 
          ")"}]}]}], ")"}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{
        RowBox[{
         RowBox[{"-", "x"}], "/", 
         RowBox[{"(", 
          RowBox[{"4", "-", "x"}], ")"}]}], "/", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"b", "^", "2"}], "*", 
          RowBox[{"a", "^", "2"}]}], ")"}]}], "]"}]}], " ", "-", " ", 
     RowBox[{"0.99", "*", 
      RowBox[{"1", "/", 
       RowBox[{"(", 
        RowBox[{"a", "*", 
         RowBox[{"b", "^", "2"}]}], ")"}]}]}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "1000"}], "}"}]}], "]"}], 
  "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.397508154431675*^9, 3.397508291441441*^9}, {
  3.397508322938101*^9, 3.397508383371377*^9}, {3.397508437391191*^9, 
  3.397508482133613*^9}, {3.397508657859058*^9, 3.397508684729219*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "::", "\<\"nlnum\"\>"}], 
  RowBox[{
  ":", " "}], "\<\"The function value \\!\\({\\(\\(-\\(\\(0.99`\\/\\(a\\\\ \
b\\^2\\)\\)\\)\\)\\) + \\(2.`\\\\ \\(\[LeftSkeleton] 18 \
\[RightSkeleton]\\)\\^\\(\\(\[LeftSkeleton] 18 \[RightSkeleton]\\)\\/\\(\
\[LeftSkeleton] 1 \[RightSkeleton]\\)\\)\\\\ a\\)\\/\\(\\(\\(2.`\\\\ \
a\\^2\\\\ b\\^2\\)\\) + \\(\\(500.`\\\\ \\(\\((\\(\[LeftSkeleton] 1 \
\[RightSkeleton]\\))\\)\\)\\)\\)\\)}\\) is not a list of numbers with \
dimensions \\!\\({1}\\) at \\!\\({x}\\) = \\!\\({1000.`}\\).\"\>"}]], \
"Message", "MSG",
 CellChangeTimes->{3.397508385464088*^9, 3.39750848890637*^9, 
  3.397508689937559*^9}],

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{
    FractionBox[
     RowBox[{
      RowBox[{"(", 
       RowBox[{"2", " ", "a"}], ")"}], " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"-", 
        FractionBox["x", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"4", "-", "x"}], ")"}], " ", 
          RowBox[{"(", 
           RowBox[{
            SuperscriptBox["b", "2"], " ", 
            SuperscriptBox["a", "2"]}], ")"}]}]]}]]}], 
     RowBox[{
      RowBox[{"2", " ", 
       SuperscriptBox["b", "2"], " ", 
       SuperscriptBox["a", "2"]}], "+", 
      RowBox[{
       FractionBox["1", "2"], " ", 
       RowBox[{"(", 
        RowBox[{"1", "-", 
         RowBox[{
          SuperscriptBox["b", "2"], " ", 
          SuperscriptBox["a", "2"]}]}], ")"}], " ", "x"}]}]], "-", 
    FractionBox["0.99`", 
     RowBox[{"a", " ", 
      SuperscriptBox["b", "2"]}]]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "1000"}], "}"}]}], "]"}]], "Output",
 CellChangeTimes->{3.397508385497651*^9, 3.397508488934333*^9, 
  3.397508689969336*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"help", " ", "plot"}], "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.397509142796515*^9, 3.397509144389314*^9}}],

Cell[BoxData[
 RowBox[{"help", " ", "plot"}]], "Output",
 CellChangeTimes->{3.397509146305434*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Evaluate", "[", 
    RowBox[{"Table", "[", 
     RowBox[{
      RowBox[{"2", "*", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"1", "/", 
          RowBox[{"2", "^", "n"}]}], ")"}], "/", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"(", 
               RowBox[{"1.25", "/", 
                RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
            ")"}], "*", 
           RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{"Tan", "[", 
             RowBox[{"x", "/", "2"}], "]"}], "/", 
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
        "]"}]}], ",", 
      RowBox[{"{", 
       RowBox[{"n", ",", "1", ",", "3"}], "}"}]}], "]"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.397509365306243*^9, 3.397509485264236*^9}, {
   3.397509896853386*^9, 3.397509906371891*^9}, {3.397509941164777*^9, 
   3.397510005069422*^9}, {3.397510064540455*^9, 3.397510136423033*^9}, 
   3.397510189153407*^9, {3.397510264855134*^9, 3.397510269189009*^9}, {
   3.397510478337304*^9, 3.397510478523494*^9}, {3.397510623543562*^9, 
   3.39751064776039*^9}, {3.397510685352877*^9, 3.397510800556434*^9}, {
   3.397510839944301*^9, 3.397510860741274*^9}, 3.397510942965475*^9, {
   3.397511216945909*^9, 3.397511223757897*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxN13c4lf8fP/AzbltDRqVhRQjZSue+X28+RlEyMip7lDSMhCJNuxQhSigz
sndmRUZGUWYiiZLMY6/f+V3X7/p9O3+ccz2u933u8Xy/3q/7egvZOhs6UEgk
kifj6//+UqvYW34ouRK2PFna36/RQfR35aHdj46D4BrPej/DSzn77bvDreDq
E2vRrwznzsEXrqyzYGkR/voLwz95HBeKwp0hL+9VZRPD97bXb8gquwzaa3ly
bxhOETePJ2V5Qs/Tl9z5DFerTMoaJXgDX3+k/QuGe7Tuvk0OvwGB3L57Hvzf
60lySvq8vQXxPueMrjIcIN/hllx2B5KMraesGeZRTShrKfCD/E/n1zQZfq7m
hC1kBkDRjqhr4gzLHFE8JpQaBKdMRh1YGS7TX4vUSQgBjlj36p9X6fDFKnzv
s/AH8DzQ+l00w7kKMgd+1D6El6r95y8x7Kny6Kvn2zAY3dByR41hDCxEn5c9
AtNPiDLgRYdG9bcNSiURUBn42zGD4TCtvZcaCyKhcEIX3BnerTdVNJP5GMyW
ww6tedJhyMDkdGB6NNwWemFTxXCGcdn6ztQY4F6qmb/O8AELv8NaCU8Bs0tx
n/Ggg+GF7T3R4fFQ5FmXX3WFDpwHoCpKOwHY240tLjA8WerK9b02Aa7KdXry
MVxU0VF45e1zeHleiWTnTof/ahPW4soSIahTzLbPjQ5i2u36vw8mQfPDDY+v
MMzewJSoUJIEObJMBAfDH5uctOsLkuG7Qf2gjCsdLD4rPpzKTAWdpUP3TJ3p
gEzODh6SSoNRLjWT3kt02NMVo+ifngZpx/IemTM82rvWxZ/6EkIXos+ZXmTk
96NeSCMhA15MjPrLnGfkM22eHxWeDVv4rYpsz9DhPu8TWvWGHNhgtKs924EO
bbl+AkqGOWBbM05ftKfD6VHzn7t7c+D+mw1H/OzocOk0h+v0WC58FzSheVnT
IQJ3DIzZXAA8B4VjW0/Sobvb6PxG4wIQcr4v/9eMkb8H6N2JKYDPG161szCc
msXHc1G4EMYKo1UUTejwWqA2HikWweXXIWHnDOnQTxYuHjEtgXHXX2NaOozn
i9vwxDy2BLKfplsrHaGDo+qiz6eBEuBuZh0WPEyHabeP6mXnSoGovrF3QpNR
H0O+LaHer0Hx9p9wRzU6SL7v/akUXw6Cr118WlXocKhWh139cjV4Hfhu7SpM
h82fU1pVHlUDu2yu4w4hRn0MUiKl86tB/dK9qbcCdAgllQlsn6mGVhmXQPZd
dBg8tE9p0u0NPL7v3O29lQ6BeRzWcW5vYajH7MYIBx064psKl1xrIGnbxJvh
6RnIyBL3ngyrAY/DsYtqUzNws+IuGs6tAfFJ25onEzMg0Uv78GmqBua+lfBq
js2AD1/mQJprLehZ7iz1+TkDIvfvc5i6vgdZQdlwr84ZcLmmZ5PvUg/0qgzF
1NIZ0LlES2N9WA9Msa+7q4oZx9tKTlhk1wN3fgLRUTgDHUeYr7OO10MEU6bO
Su4M4Nsroy3ON4AhB+sN6fQZYC+R/shyphGYnsjP7nkyA8mznGB+ugkq4j4L
XPSagYslDqEUkY+QoLc0fk9mhrGeDQTJih/hcnqL6vC+GZjspuWta3wESsMF
flxiBtyXuTtWznyE6+9PxfwQmYFrxNtd8+kfwaHuWgH39hnwr9md+Uf+E5S2
mZqQqTOQ8LHzw2f1NnihsUOM/8s0fP51hC3V9jNE2PTr33GbhuD9c6Sik12w
Q+inkUTSFLjuq4+sTv4KQjHaN2dTJ2HJ7nxW36UBKCwlGXbJTYBthYn+wzOD
oN6bHWy/7S/YTX2urg4cgtVH32Q/lI7CPdli5xT/YZAJGyX6PX4BpbpY5e61
X3D6I3usIG0YuCR1W/qjR8HkqFm6UscPOByvnjgZPgbnmZ6KMKV8h60TTVo3
isdh2uXvkVsl3+BJ3Wsy9dwkePlrOJhc7gHaLrV1QfspUB55emSpoAP2DWwe
uu4+Da1veHR9p9ogM22LY6HbDPxOU/7p59UKPt8s2vf508EG+N05VBvAlXZA
Ny5iFtzyhN4sdryDpXgN2z8P52C4oy7XbbESiHk8XC5yDhSdn1+831EJt/RU
3nrGzIGOy50z1fmVwLoqIYy9mINnAe7MzpcqgffUpsGd+YyXhJpT5fhQBcjy
9NjofZkDznKW31c6ysEh0Nkmd/s8RA1pTj/48Bo+ujyx9nwxD/ed2bwOrBaB
5MPNy+4p8zA8NSGvNFgEd7L9I93S5+HlY47jWnVFoDzu1ngxbx7EekOeJocV
wbPzuor2b+dBc1fWNrO9ReB0ZoXFYJBx/qAa4SCTQsDMLbMlhRfg8XPLkdV3
+XBQW3it7/kCCCyYGEn35IBiYmNgXfICfDp5Szy0Jgdk1t24c18uQPBDCxdy
dg4IF78Tv5u7ADyyNeoCd3OAY6+DkeSbBTh2CTutsj8H+pjT0jwGFiBrnMT9
kisbbr2XNtoksAjbH6lwKT96BT7CHX0LwouQkTaZ73vhFXj4+joOii0CZ2J6
06jmK3BSbr1eKLMIZ+w7ZKQXM8AoxSXtNLEIZqeJUydtMkDUP3811WIRTGbz
NDUOpEOD5sE0FLsIE5HDqWykNPCq85W5kbAIA3eDVyp7UkH8SE1BRdIioMxO
gdjCVPA/evyNauYivO5MCmk+nwoaRg49ipWLoPBsFePoSYFq6zBOiYFFeMRp
kTtQkQzF3r9duPYswfmyi4evvEiEM6sy88fFl+C/1/eWSbcTge+G+/VQqSVg
nfolnmeTCO6314M4lJZAbKQ58a5QIsgH8SYyaS1BKHZsauTFC8iKUvuyeHYJ
3NR2uke9eg7JuTEHBzOWgHKAk5WtKB6clk9LdmUvQcCW65m/b8WDrObuHS35
S6DmyrSXRS8eyrterJSWLQFfdy7HwnActK9nVIV9WALjgZymzB1xQNar1FT7
swQ6tjeu6TyMBYvRQYMEyWUQ8d2pezw5BoQVk9WjZJbBTF9hxs8rBn5dP6tw
T34ZMvL3LdB1Y8Cda4zHS3UZuof9/bxnoiHkwGzncZ1l0CJjSWKa0VDqz2K5
fm4ZfHKmXT5PRwGviJST5ctl+NUm4h3gEQEPw0NMXmYug9sfyQGjYxHATvmj
Ts9dhvmSDxPmeyKA9P3ljuDXy/C3kkN3T/sjGIvb21z4YRkym5Mf3VZ4BDX8
IrIbxpehqo+mb7geBu5b+OfK5FdA/taXv7V3HsDErauDzCorIOkRUtwAD8Bp
qqvF4NAKtFRJn1NdCQXrj49TR/5bAQyTn7L2CIWjobwnuY1XYHRXT0ix830Q
Yecqd/JcAbcAu+vyHiHQRma9vb18Bep2c32IaQ2A8cwYS/3qFUBHThl5xgQA
26l9hwJqVuBEnk1crl0AoDw9Or1pBdiYWpZVF/0hyzbyzMe+FaCJn9CLEveH
kHfCugHrK3A16YPUjui7oOGH88yqrwK9/sDHiuJbYC3XOrlPexU0O3mirt67
Bd591s22uqtQIeMs7G9zC/KU7vp/NFoFq+c/uR5y3gLB4caFDPtViC69MGx+
5iasaJn12fqvQnuN+thGA18oZL2c8rFhFRZejvDwN1yFYZ9bfyubV0G6u05u
IOgqbJt6oJj5aRXu4LKeu3Wvgk/3q7dB3asgWvp3D7nVCzTSh7+p/16F2J61
Yr2vntCme2prIesaLIW4vQnk9ACs2tEykXMN+GnaKSGfr4Cyomdy2OY14D3G
6bIaewWe7IxQuLRtDfZHzDru238FbP42H98rvgZp0puWE8zcYTJULTBGew1C
DwpUXa5yA2GqfmuA7hpMnef4IhjqBic8Lfk8jq/BmY/LtQoWblBi5Z1kaLoG
Ri3H1gNXXOGGbGE1x9k1UNZ/qvsdXGFjm/jidf81+E9Uc29srjNI8W52sq1d
A8knEhtj452AO7vsVXLDGjCdLf+4fMwJlg6fnfjVvAY5mkE+wqvnoN6n0t25
Yw0KHq9oVVmcA/uhCzd8RtZAq+bNNy5xR3iW3xARxbYOY7Z3mBb6HeDusSud
3RvWYZFza7vEEwe4MCLIv2vLOoj9zOrcYOwAqju84hP512H37nifkSZ76Lgt
lp6zbx1GfTftr6yxg42Gd6oaj63DobYfN4fabWD2jwxlo+E6zG9q6k6KtoGv
fj0aBibrcEftTDXV0gbSS+UaOy3XIX6h2C161Bq0hAY+DzmvQwxmcHyF3Rp8
J2mja2HrsEyU3DNoNQeH4F9S6lHroCYWVx183hyO7olw9nuyDrsELi/1spoD
v9kfOkfiOiQ63r9XoXUaiqpi1rcVrMPkThM2aD0JE6FzPAod63Bx1PC4IZcp
jE3ufivdsw73xj4pBLwzgVFDbWfxb+sw1dOyEuZhAkN80Q27htdhrrTbTbjf
GHriDvqyzq3DhafDneulJ8DWtHJmnJ2E4k5Y8ahGGoJNoKHOGCcJvdu8+JTp
hCFYlw4n/N5IQvu4u6rvcRuCxY5NekNbSMjkxKmIuggDMOu3SuvmJ6HZuYLM
d/H6cOws2aJGkoQOhBaOrbw6BkejI/PfSJEQv/H5a5HoGOg0SLBXyZDQaVWH
J+5fjsLhfYbFpfIkNOPtPrVEOQrqEy+4slVJKHG9yafzgg4c8NR4H6NDQpI+
CQInr2qDSlrXzsdHGf8/b23GLKgNyt0XLkfokdCv5nC35jotUDgUKfjAkIR2
M+elx/FrMd6HP6/dPUVCD9+TkqnNGiASELDf2YmENvxhyom2VQe3DkVf2wsk
JLH/6mv+HepQLTrYZHyJhMInqVF3P6uBZQ3NieZGQqP7m18x66jBE/J0Ets1
Enoi0xbrBwi2+JjzJwWRkNwcSZYtmQY2H9jOPQ4hIQX97t+zsjTI4S8uDr7P
OP+25tkLlYdAr5TL2DWMhFCvSubvPlUInnv/gIghIZbLZR9eyRwEiqscU3ca
CQVSTxaPciuDQfU3o6Z0EtI3fiv1vEgJEjbde1H1ioSCmsvbEk8pAZE1DCk5
JGRxNm73jRRFuPbn6bXLJSSU5HqXkDimANMOzJMb6klI/a+aL9EuC2qF+QS5
kYQCbi/KcQXJwkPM5j79AwldPML5dwFkQSaxTLK3lYQadiYfmLXZD04DLg5p
nSQU0msS/pWQhsFTvT3qIyQk2Bfi32oiAZy4aar1bxL6TM+PM+4SByWB9su+
f0goL0faYva0OAT+aOR8PUFCBo9KBBzO7YX9F14TcgskVN6l3YxiRcFMT5nj
+BIJ2TlGZrVIi8Jt2bzOCyskNOhyKI54swc66C9d0khkpOgmLJz+VwR8rse8
EGAjI1Or3+WLp4UhxYrXGecgo9sjkk++LwtBq1rYodMbyEhULHOf1zMhEGYO
+hzFRUb1pdSF6J+CUB/qxbyRn4z0bHEZ6hYB4E0wdVqRJKNouzS8SYYfiNvt
yvzSZDSVhPwW47aDo/1x6oH9ZNTSDfQWru1QLq4de1mBjMpcjksdWd8KtrnK
LaOHyEiV2a7QZoEX7j3Ke8JKkJF0mwlfkQ8vFF6ROSuGyGjPx1xrOyovsKqK
kWw1yKgW11BO3MoDWW955buPktFAyX9pxae2QFdS2NqcHhk5LYccb5vkAnLA
hg88BmSU2axUsRrIBSd0mez1jclo9r/T3+2rNsNyOz2yzoKMTstJJG8N2AiH
f7YvFl4io2c1syJPNdjg+r5Q72wXMhI7ynnEr5AV8lwPr6a5kdGWovdishKs
sGOtnBTrQUY5+8L+PtnGAuN8KSy3fRl5OCU/ecjHBCIW1kHeN8low+B+L91Y
DMwS+Tmu3CYjDP10cNmDwZv9DzY6+pPRFbp1ZushKkQc9uLVCyWjg/FKPc1+
ZGgIlX+s/ZCMhjsMVd7uIsPa57FtauFkJHJpk2dbMQnO2tjsVIwio1sXt/X+
N7ROqF7TEeGPI6OicAN7ptUVYiBjp9xwJhnJ8Ou+qeibJ3inO/L6sxn5HPmZ
yXJkntA5EKbYncsYt/ggdqN4jsivYTrQVEhGh2s5WcqfzRL+feNEXgUZlbqy
any7P0OUibyszqgiI6Mb0W1Urhli8pydevIbMjpOlf45HDVNnJzr1IyuJaPt
D3Udc9OnCKlNb476NpNRR3Dt1Oj3CcLG2LvFs5WM6lp1X2pxTRBRT5X0XT+R
UYnH6wQTzXFifW+6kf0XxvlLNJaUy8aINvTolE4f4/iD20f8e38TLAHHvv7X
T0bFdblPN8n8JmjNLJb4d8bz1z+nPrv7i0g+6WMj+5OM/tuz8swdHyG83Bwc
+f6S0Q3wXZzoHSICdcfPqk6Q0d+mllv30RDxeI/nWcspMgqtP9Ap9fIHUdQR
eCZlloyW6tVO8fkPEjOqr+yV18ho6I91uNyFAYLCo2R/ikRBhdrsb8a/9hNb
/lbY+VIoKM5Y5a74r2+EbHyr7XtmCmrdan+efUsfcYk6Y22yiYKWRvOmzmd3
E9e/eltf46Igt3FahvbPLuJeIWYdx01BUtwe5FeCXUTGWT6r4a0UZCyo1hGY
2kH8+nDQwkOQgoLTBbI2TbcTC0lvzZ8IU9C1tB270vTbCRZfXfPKPRT0DWu3
bMlvI8RkLU4zS1DQwtGVSMOAT4RdxM2TUXIUVH30uqR3dQvhdpHt5GsFCtoj
L6AfWN1M3NYKN/umREHR51tNWOqbiISFRFMxVQpqv9n48slYI5HzScpUh0ZB
Y1V2RgZsjURVeqHJJYKC3nIIPqyUaiC+mdcZF6lTEH/5HlPOgDrir5K+cY8G
Bfk7+214XPGeWNnYfWJNi4L+crClSi3VEjvejBpp6VLQiGvzesfdGsJMdKNh
hxEFNdhMUCd63xCOa1EGS8YU1Mz2fUsY8Ybw7BQw2G1GQbJDhq5cKdVEVJCc
/hlzCjLc4zN1lLmKSLZ9fTzYkoKYjLK9ZyYriIJD/x3Psqag6383sxgMlRPt
f0/ozdlTkPlWQ/qhodfE4Pu+Y/xnKShf0tPYcLKUmI4/c4w4R0EHN+emyWGl
xGZDr6P+FymIZ7bT9IJ6MaFX9FSHz4OCtl23b6NyFxCOM7brvF4UZCE7yffO
Lp+4IytZwHuNgiJEK06PlOYRJeklu3h9KeiPIiW44Uou0TZyo43nJuP4I68n
iN4c4u8e7QCe2xR08vtvzUDNHEI4/ssktz8FidrYft6ln0XQvsYmcwdSEMvC
0Sc8KJMw3W5/ijuYgkIP/bybceAVce/R9LstoRRG/2zlf6eeTswFbHrMFUVB
HB81iqQKUojNtR26XNEUdOIB3/7MwWRiHyWOxPWEghTv/Sln2pZMWPtIOW2O
o6Cq2qVB96hE4lrpzO7NCRQ0HEgLkuh/QUTOvW7f9IKCdNwMjKalXxCNLkfw
TSkU9KanqZatL4EYytw8vTGNgt55795EwhOI9dHOlI3pFLSpRdMuXyOeUHQ4
s3ljFgWJXRzlEF2MJeJO3vnBWURBZ3jH6BlfoomSKJ1ozhIKKn/GG6T04zHR
3s51jPM1Bd0e/KMpsRhFsOolFHFUUhBb1ZMqTTySEA45e56jmoIUaCPK404R
BF4vI8jxljGupKVCSnhEuKlXBLG/p6BctzbuywLhxL0bdwn2ego6F/BCxOZc
GJFarjvD1khBkTOpm9tLHxJflXvM2VooyLaDtPVrTyihtW9+P2sHBcWydlxh
VgwmrB0rh1i6KKhxtvXXJtEgwjvZL4alh4IG9I2PbRcMJHIEeKgs3yjowfPt
73vk/YlG895i5gEKcn0/Zj95xI/4GfPiAvMgBR3YX/On+txdgp9HroNpmILs
X2ban317m1A0WAhm+kVBLg1MBzKXbhHHQ6uAaZSCnE/cj7mveou4y6r3Ehun
IKPbRd8kEm4Q4ytOPtQ5Cvr02uVVV9Q14qSZrsTiPAVN6zIxjXhdJWry93WM
L1KQtNanW4sOXkSM09j+nlVGnp11BslWHgT2vulr6zqj3l8VGNw5f4W4JJQZ
VEumotNVB1LHb7oTGl0Xf+QwUZEPE9dX3jo3IltB72EKCxWlzNMLpOZdCf4H
MngsGxUFuJXm+u93JSY1J6ICNlDRZWllllfOzsTTfBcdS14qqtI16dAmnAjm
TQbzRlupqFuEv5yF+xzh4iSXdGQ7FeXVCZZz0s8SWkLTq4q7qMiEWJPm63Yg
cn3a0iUFqOjEwDZN2ld7YmdXnqmgEBVNfh8KHP1tR0yHXs7lEKUi+RDtLB0R
W8Ji1MiSvJeKXmpuS1DVsyHqNRU55sWpaFs+3yuZ29bEsxW6/aAUFZ0/Jc3v
x2JJsJp94eqSoaKDb4pPXX5uTrjlF1Y2y1LRQODRhPc6p4nDTh7bShWpyHde
iv1AgxmRX2tSm6VMRSKsau5yz0yJ3UIqbkkHqOjX3OUdWr4mxEzn/IcHNEY+
93Op2Q4nCEuFLi8/gopWFWXJzOeNiPrQElFvREUlezzOXfc2JOI0r944o0FF
P/jYiqjl+gTb85NS5lpUpO/oKOfScZxwXznYbXCYii503iCytfWII/lL8vhR
xvUIlp6nVrpEwcbefnk9KvpjI3X5E6ZD7HYquyeuT0XGxsTkWOlhgi7oM8x9
gopcBcnVsgZahJWP+SM2EyqaZ2eJ4pPXJBo7aWjdlDG/a9qj5oIaRHzoaszo
aSoK3/Mto05YnWAf7dMasKCinAcb9bqU1Ah3zcqZL1ZUJFr43FPoBCJ0VnyP
vbGjomP3xHv6rHGi0NRqqciBihqGkOTm3kOEYD6kvjpLRaYtSI/ZUZWYO0ci
R5+not0bpCvpRSqETe1A5v2LVOTd+9TYwlOZaBJ8c+qOMxVd5aBWn9NWIp53
3iq4dJmK7B2E7ydxKxDDtbL9oVeoqPK7+NTKghwhVdDPlu1JRT9HMO0Hf2WJ
ooe41YQ3FamJbUlpoMgQK75jQZt8qQjL116/TkgRahefFuy/SUVMWUQR6ZEk
0XRkkc3lLhUdWtFR9L61l9hyIE3xoT8VdWqI6O3cLkaYipla5QRSURyzhmpf
zR5ikFJYMHmPMT7G5J50QpgQn7Lr3/yAijqWh+3KlYWIi/1b2OXCqChoZZcd
n4QgsVDmYuUaSUVrXvcarTx2EkS6QHDYYyq6lP6uNDePn7gT3VKQG0NF1ofZ
vuxj207U+1/v//SUitzZE1TOem0lNl6RYp9+RkVZ78LDNq7zEkZ2vYpbEqgo
e1O5Td9THiLaINhK/gVjfkrOqcQf4yZEZH4VuKVQESVwHDz+bCYcdz7uD0+j
osPsArLd6ZuILHYt9vx0KuIUIY9KJ2wgZhboiu2vqOho3TDPxkIO4sBIotVM
FhWNhHW4Fo6wEb5fDIO5c6noOaG14qHMSrx7Ry5UyKeiEJ7gjrJ4ZkIvwYrd
vZiR34Jg/NcyKhERulEpopRRb7LONybPU4hunwqrgjIqOhmQWjwrSyZ2n78Q
/LmCijJi+e4UspEI+5M7CulVjPm78e4U9+gq/lK7sZ/nLRWF3qgKKf6xjI8r
XWVXqqGir2ZWxYfXFvGrWzqtrtQz8jIuLrsTOodXkvyDIxupiP3+3clo0iyO
TSgWFjYx6nPH5AHnezP4kb4f/V9aqEhSZCfdS3YaD/0Qzj73kYoMPkTEEX8m
8c+lakp87Yz+YLrbscxjAt+eNmml/IVxf0J8tE3wF0+6q1fo0c2o34x1fYL4
jY+6rfZH9TLq59CRuAiXEXy/zSv24j5GntFpnDNvfuLux08rdfZTUW9wx9QZ
2SH8Nc5uPf+diiLGxaL4Xw/i6/tKg7cOURFbwFSGkcV3XIPfsVBlmIric2K6
XbcN4K1ztexeo1REnTwrmpHQi/P8dFeKHqMi3fCfq/ER3fipdhHrknHG/L7S
jZPO7MTj37QFd01SEZ9UcvHEyBd8KPtW4cI0FSmXiG5NVf+MS8bJDmybpaLN
l2qjVMracOd7/ewH56noXbiyeMrxT/iSI259dZmKooUolo+DmnGdMkl0ZZWR
39sR3pxzH/CnG7YJuq5TkYTkQmXhpQZ8zIqJdJGMoY57zrl6UXU4LW+635GK
odki5T6Nb7X4PWygyp4JQ7e+xvbc0ajB+0ya461ZMGTq5Mi9te4t7rucamXG
gaE8ysr9le3VeMuxSDixAUODu/W7RpsrcIGE2wL6mzBUtNPYePujMtxl2nld
lwtD56z8rqfdLMWrNSz6tbkxdG2Hp9nvR8U412Odqv94MfSr69M108ZC3Pa3
SjxsxZCen0B0lFABTg3dYqWyA0OfumI8P0nk4icG1gmFXRj6ejNROjwzG0+S
/7t7vwCGjl1Rr2M/mInP3u1ZkxTC0Lw3U1/SdDqu1Vn3TUwEQ46iziGynWl4
lERhpbAohh575D7O+5GCj3i/iNu9F0N7FQd1bHiT8UDB65Z8+zAkM/A5l/rt
Od7l5kRskcYQy7UdMWouCbhErenujfsxFL63qsGDFodf26q5xiaHoeyTj9dG
PzzFG8/Jf2NSwJD7A71IqZAYnL9coJKshCF5boKj3uMxfn7jhrhVZQzFCF2O
9QuJxDnzRyxmVRm7RQ4bt9g94bg50xd8ioahS2e2HnqY+BDPNH276y+BoZMU
GeuXt0LxtZfZq78Yu8sD/4lbGtBDcL2V2L4hdca4woWC4SdBeJxecMWABoaa
9+rM3XYNwCcSPJ991cLQ7d71Hf7ufvhDTUOLzzoY+u+av4/f9C184DHgH48y
8pZ1u3T17E1cblRqV5MehqRkaiI9F6/jt2n8q3X6GBKNzRaNsfLG20JZ+t4Z
Yih/VTO3YMULF/5OL686gaEKtjxp3yYP/LLCYGyZCYaWbv25vNTojtf4tfoU
m2EoucM//yrdDefpKjfPP4Uhz80xEK7pittLptOyzTEUF7tsreLhjBf6PN6Z
YYkhth/CGSeSLuDMrXdXUqwxVFnsMMS72Qk3EXL7+sIWQy3b8DvXC87iKZet
yuPsMRTF/f3axD0HfL72aOyTM4z/f0rRlIy0ww9vU/WJcsTQtk3yDoxNCB7t
tNc83IlR3/WnDMJFrfFf5Ty00AsYMsB548KOWeAHN1F2Bl/CkLTRWYP4R6fw
YJuJZT8XRv2MFd99vtUM78n/2nvLDUP3MneyWH02xvcxN5Zdd2fUY0uSCFut
Ee5jVvz0qgeGXvxRylT4aYA3pSd5X/HCkFv1+8fNsvr4rtWw067XMLSQ9nuf
4uFj+OHBY6WPfTDUXSXpwE/o4O51bFsrfTGk+HrPFtlb2nj8q1r3oZuMPLnl
1/exa+KNYbfa2O9gKHDtZPL5NnV81gOXlfPD0HqlovjPdoQLmi/eNw3A0DfJ
rm7FLQSuq1b453oQY328Z7vA36OKe4i5HkkKYTzP2d82jnMq+HMO6dTG+xhq
aAut+26phDdN/sKmHmCIb/PDz5ycCvjClyTbreEYKv/sNSw0L4uLlFlX4xEY
on/EK+YVZHC9hJ277aMwtDudGsb9TRK/5tflHRyNocW+q1Z3BvfiyU4R3TlP
MKRzKXanxAFR/ONxfZXOWAx1nZbwft8hjC8rckauxmFIOKIv41eRIC7GXz8t
8pwxH6a0lxmJu3CD9Tv6OomM9ZTXdHBBnR/3GYIsl2QM3c9OtqxBW/HUhmWO
x6mM/PXoe+Qf8eBtWcXnKl5iaNf579cs5bbga48u1/3IwJCHSm3sEe7NuMTV
/aLsWRj6O2sgc8eOEz9h+ee2bA6j/vCHds842fCb/6UOmOQx+pnZHuX/+Jjx
DHE74noBhlKVQyyYPah4xwaB2MQixvrRV3YKESbj5JmexYYSDL33jh7tE1uj
SXVFmU6+ZqyPeonQU7eXaKYVhoV8FRiqG/7hvU1nnnb7xUZuvApDCW67Aje6
0WmZAY0udm8wlMTeq3ttYorWdcG/JegdhnJ8Un19XSdoVEN1qZxaRn/yaPwV
FvyHJqOyFtRRx6jfs6lGA/y/aCd3vh5ZaWD0g9KdYzU8P2l3yR6aIk0Yeuut
+nTbhUFazrBc4pEWxv2pVZmz8w3Qej/8Jbl8ZPS3quDZOa6vNObcl5ZRbYx+
HeaWXOnVRZOPcigv/4whh1fC8TSDLzQLbyH+Hx0YOiNNipm/30YLtO7zZOvG
0NXbmxVXhT/S8jVjvuzvxZC+8VKkM0cT7ZuksYJJH2N+ZHOFw07W09g2c4X5
9DPeN6c75D4I1NIUZ5vGX3zH0MWZzBKP429pwVUa6RM/MZQrdnes3rWMNhBU
7kAbxZDYK9nYvTcKaBzOXu9sxzA0EWgUnJqTS1M+oSgUNI4hVl7J99K3s2j3
d7/6+mUaQ1aJb4N+xafQSqiOqit0DHUGC4QsuifShn6JRAvPY8hZxEE/sziB
ppr/1Mh5GUPD65d+mT2Lpg1rhzSyYkyM/dEfjgGbYJqtrrWgKDMTqjdr5Q6K
9Kf16Sl5qLEyIRFq3FCw/h3aZ+N+oWucTMgs8NxRPykf2ls7hat/eJjQw5qc
lU8JF2nPbvTubRFlQjp8M1uSDh6nnSje5/dImwm5Zf3VfCDBSXsn1gS7Q5hQ
sMTGHGlF10NOrCmYEBsz0tui2ysl+e1gccIe/F0YM2qIX+ffxcyq0nKIVmvI
xYLIfQruCeL75BecnhpZh7KgnrDgDyXLSLxeP954Ax8rSmNqjIkp5Wa3PUhL
TY1gRaT/93nRdf3C911s/99S/kvtU/+4SMHzEGX3//wh1IVd5B/TNezS7P+x
Vu7hoZF/PBrEbT4u8D+7qzx8t/aP14Y4920S/J+5EfPS/n9Mm1t47PqPQ22/
tdP/8bbNpw8xCf3PLyo6X/D+4+Jtn1yV//FAy7tNXv/YyQd5Bv5jukTFt+h/
zOpXlFn6j8PlFXgb//HOgWyfnn+ccl9qaPQfyx16qbv8j/8PtniLTg==
     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxN13k0Fv8bN/DBHVIqZE22FMlSCNU9cw0JZckuS0K2JKFshUrJErIXZd9F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     "]]}, 
   {Hue[0.14213595499957954`, 0.6, 0.6], LineBox[CompressedData["
1:eJxN13c8l9//OH47KWWHJKuIjJD5vK7HMzKKbFJWiEoSsrJKRpIkq8jeI4Ws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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  ImageMargins->{{0., 491.}, {250., 0.}},
  ImageSize->{Automatic, 637.9841580399427},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.397510193529083*^9, 3.397510271432427*^9, 3.397510481123699*^9, {
   3.39751063007122*^9, 3.397510650060003*^9}, 3.397510810131534*^9, 
   3.397510863901481*^9, 3.397510948068427*^9, 3.397511225234825*^9},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Evaluate", "[", 
    RowBox[{"Table", "[", 
     RowBox[{
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", "x", "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}], 
      ",", 
      RowBox[{"{", 
       RowBox[{"n", ",", "1", ",", "3"}], "}"}]}], "]"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.397510964665713*^9, 3.397511007443741*^9}, 
   3.397511058993198*^9, {3.397511171244306*^9, 3.397511193633975*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw923k4VN//APAZxFgKhRCyfZAkIevMfV8SLZItSbZsSRIiOy1EKtmylDVC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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJw8mnk4VP/7/2fG2EtZKlkiCVnSQqg5536FpEjv7GWXkCiUJVtItkL2yL63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     "]]}, 
   {Hue[0.14213595499957954`, 0.6, 0.6], LineBox[CompressedData["
1:eJw922k4Vd/7MHCcwUGDMSXJlFKkDKHO3vcKqaRIhcyhFA3IkLEoQ5IMEcqc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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.397511060736416*^9, {3.397511174108455*^9, 3.397511194548768*^9}},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{"Evaluate", "[", 
    RowBox[{"Table", "[", 
     RowBox[{
      RowBox[{"2", "*", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"1", "/", 
          RowBox[{"2", "^", "n"}]}], ")"}], "/", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"(", 
               RowBox[{"1.25", "/", 
                RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
            ")"}], "*", 
           RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{"Tan", "[", 
             RowBox[{"x", "/", "2"}], "]"}], "/", 
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
        "]"}]}], ",", 
      RowBox[{"{", 
       RowBox[{"n", ",", "1", ",", "3"}], "}"}]}], "]"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.397511723968065*^9, 3.397511744500734*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "::", "\<\"nveq\"\>"}], 
  RowBox[{
  ":", " "}], "\<\"The number of equations does not match the number of \
variables in \
\\!\\(FindRoot[\\(\\(\\(\\({\[ExponentialE]\\^\\(\\(\\(-2.5600000000000005`\\)\
\\)\\\\ \\(\[LeftSkeleton] 1 \[RightSkeleton]\\)\\^2\\)\\/\\(\\(\\(1.390625` \
\[InvisibleSpace]\\)\\) - \\(\\(0.609375`\\\\ \\(\\(Cos[x]\\)\\)\\)\\)\\), \
\[ExponentialE]\\^\\(\[LeftSkeleton] 1 \[RightSkeleton]\\)\\/\\(2\\\\ \\(\\((\
\\(\\(\\(\[LeftSkeleton] 11 \[RightSkeleton]\\) \[InvisibleSpace]\\)\\) - \\(\
\\(\[LeftSkeleton] 1 \[RightSkeleton]\\)\\))\\)\\)\\), \
\[ExponentialE]\\^\\(\\(\\(-40.96000000000001`\\)\\)\\\\ \
\\(\\(\[LeftSkeleton] 1 \[RightSkeleton]\\)\\)\\)\\/\\(4\\\\ \
\\(\\((\\(\\(1.0244140625` \[InvisibleSpace]\\)\\) - \\(\\(0.9755859375`\\\\ \
\\(\\(Cos[x]\\)\\)\\)\\))\\)\\)\\)}\\)\\), \\(\\({x, 0, \
\[Pi]}\\)\\)\\)\\)]\\).\"\>"}]], "Message", "MSG",
 CellChangeTimes->{3.397511745998757*^9}],

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     FractionBox[
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{
        RowBox[{"-", "2.5600000000000005`"}], " ", 
        SuperscriptBox[
         RowBox[{"Tan", "[", 
          FractionBox["x", "2"], "]"}], "2"]}]], 
      RowBox[{"1.390625`", "\[InvisibleSpace]", "-", 
       RowBox[{"0.609375`", " ", 
        RowBox[{"Cos", "[", "x", "]"}]}]}]], ",", 
     FractionBox[
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{
        RowBox[{"-", "10.240000000000002`"}], " ", 
        SuperscriptBox[
         RowBox[{"Tan", "[", 
          FractionBox["x", "2"], "]"}], "2"]}]], 
      RowBox[{"2", " ", 
       RowBox[{"(", 
        RowBox[{"1.09765625`", "\[InvisibleSpace]", "-", 
         RowBox[{"0.90234375`", " ", 
          RowBox[{"Cos", "[", "x", "]"}]}]}], ")"}]}]], ",", 
     FractionBox[
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{
        RowBox[{"-", "40.96000000000001`"}], " ", 
        SuperscriptBox[
         RowBox[{"Tan", "[", 
          FractionBox["x", "2"], "]"}], "2"]}]], 
      RowBox[{"4", " ", 
       RowBox[{"(", 
        RowBox[{"1.0244140625`", "\[InvisibleSpace]", "-", 
         RowBox[{"0.9755859375`", " ", 
          RowBox[{"Cos", "[", "x", "]"}]}]}], ")"}]}]]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "\[Pi]"}], "}"}]}], "]"}]], "Output",
 CellChangeTimes->{3.397511746007961*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Evaluate", "[", 
    RowBox[{"Table", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"2", "*", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "/", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"(", 
                RowBox[{"1.25", "/", 
                 RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
             ")"}], "*", 
            RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
        RowBox[{"Exp", "[", 
         RowBox[{"-", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{"Tan", "[", 
              RowBox[{"x", "/", "2"}], "]"}], "/", 
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
         "]"}]}], " ", "-", " ", 
       RowBox[{"0.01", "*", 
        RowBox[{
         RowBox[{"1", "/", 
          RowBox[{"1.25", "^", "2"}]}], "/", 
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}]}]}]}], ",", 
      RowBox[{"{", 
       RowBox[{"n", ",", "1", ",", "3"}], "}"}]}], "]"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}], ",", " ", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.397511848108798*^9, 3.397511855759235*^9}, {
  3.397511900373942*^9, 3.397511991143097*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxF13k8Vev3OPBz9kFEIsMtFaFBSOaSYT0UlQoRSeZMKTKVLiIZzyEhQyhD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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxF1nk8VF8bAPDBhJSytShZi+yKUOG5qSSVomghoZSQrdBCEaFIliwziGSL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     "]]}, 
   {Hue[0.14213595499957954`, 0.6, 0.6], LineBox[CompressedData["
1:eJxF03k81FH3OHBCtmSbipItpWyVyBLORJYkCsmTJbSSbIUSRQkpkhBSJMvM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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  ImageMargins->{{0., 466.}, {93., 140.}},
  ImageSize->{966., Automatic},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{{3.397511939744956*^9, 3.397511961004385*^9}, 
   3.39751199414818*^9},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1.25", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "/", "2"}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}], 
    " ", "-", " ", 
    RowBox[{"0.01", "*", 
     RowBox[{
      RowBox[{"1", "/", 
       RowBox[{"1.25", "^", "2"}]}], "/", 
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}]}]}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.397512041619621*^9, 3.397512083164962*^9}, {
  3.397512294020013*^9, 3.397512334769715*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "::", "\<\"nveq\"\>"}], 
  RowBox[{
  ":", " "}], "\<\"The number of equations does not match the number of \
variables in \\!\\(FindRoot[\\(\\(\\(\\(\\(\\(\\(\\(-0.0064`\\)\\)\\\\ \
2\\^n\\)\\) + \\(2\\^\\(1 - n\\)\\\\ \
\[ExponentialE]\\^\\(\\(\\(-0.6400000000000001`\\)\\)\\\\ \\(\\(\
\[LeftSkeleton] 1 \[RightSkeleton]\\)\\)\\\\ \\(\[LeftSkeleton] 1 \
\[RightSkeleton]\\)\\^2\\)\\)\\/\\(1 + \\(\\(1.5625`\\\\ 2\\^\\(Times[\\(\\(\
\[LeftSkeleton] 2 \[RightSkeleton]\\)\\)]\\)\\)\\) + \\(\\(\\(\\((\\(\\(-1\\)\
\\) + \\(\\(Times[\\(\\(\[LeftSkeleton] 2 \
\[RightSkeleton]\\)\\)]\\)\\))\\)\\)\\\\ \\(\\(Cos[x]\\)\\)\\)\\)\\)\\)\\), \
\\(\\({n, 1, 3}\\)\\), \\(\\({x, 0, \[Pi]}\\)\\)\\)\\)]\\).\"\>"}]], "Message",\
 "MSG",
 CellChangeTimes->{3.397512048686859*^9, 3.397512085189294*^9}],

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{"-", "0.0064`"}], " ", 
     SuperscriptBox["2", "n"]}], "+", 
    FractionBox[
     RowBox[{
      SuperscriptBox["2", 
       RowBox[{"1", "-", "n"}]], " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{
        RowBox[{"-", "0.6400000000000001`"}], " ", 
        SuperscriptBox["2", 
         RowBox[{"2", " ", "n"}]], " ", 
        SuperscriptBox[
         RowBox[{"Tan", "[", 
          FractionBox["x", "2"], "]"}], "2"]}]]}], 
     RowBox[{"1", "+", 
      RowBox[{"1.5625`", " ", 
       SuperscriptBox["2", 
        RowBox[{
         RowBox[{"-", "2"}], " ", "n"}]]}], "+", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", 
         RowBox[{"1.5625`", " ", 
          SuperscriptBox["2", 
           RowBox[{
            RowBox[{"-", "2"}], " ", "n"}]]}]}], ")"}], " ", 
       RowBox[{"Cos", "[", "x", "]"}]}]}]]}], ",", 
   RowBox[{"{", 
    RowBox[{"n", ",", "1", ",", "3"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "\[Pi]"}], "}"}]}], "]"}]], "Output",
 CellChangeTimes->{3.397512048697417*^9, 3.397512085221879*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}],
      " ", "-", " ", 
     RowBox[{"0.01", "*", 
      RowBox[{
       RowBox[{"1", "/", 
        RowBox[{"1.25", "^", "2"}]}], "/", 
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}]}]}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}], 
  "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{3.397512351448692*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"FindRoot", "::", "\<\"nlnum\"\>"}], 
  RowBox[{
  ":", " "}], "\<\"The function value \\!\\({\\(\\(\\(\\(-0.0064`\\)\\)\\\\ \
2.`\\^n\\)\\) + \\(2.`\\^\\(\\(\\(1.` \[InvisibleSpace]\\)\\) - \\(\\(1.`\\\\ \
n\\)\\)\\)\\\\ 2.718281828459045`\\^\\(0.`\\\\ 2.`\\^\\(2.`\\\\ n\\)\\)\\)\\/\
\\(\\(\\(1.` \[InvisibleSpace]\\)\\) + \\(\\(1.5625`\\\\ \
2.`\\^\\(Times[\\(\\(\[LeftSkeleton] 2 \[RightSkeleton]\\)\\)]\\)\\)\\) + \\(\
\\(1.`\\\\ \\(\\((\\(\\(-1.`\\)\\) + \\(\\(Times[\\(\\(\[LeftSkeleton] 2 \
\[RightSkeleton]\\)\\)]\\)\\))\\)\\)\\)\\)\\)}\\) is not a list of numbers \
with dimensions \\!\\({1}\\) at \\!\\({x}\\) = \\!\\({0.`}\\).\"\>"}]], \
"Message", "MSG",
 CellChangeTimes->{3.397512353137172*^9}],

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{
    FractionBox[
     RowBox[{"2", " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"-", 
        SuperscriptBox[
         RowBox[{"(", 
          FractionBox[
           RowBox[{"Tan", "[", 
            FractionBox["x", "2"], "]"}], 
           FractionBox["1.25`", 
            SuperscriptBox["2", "n"]]], ")"}], "2"]}]]}], 
     RowBox[{
      SuperscriptBox["2", "n"], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           SuperscriptBox[
            RowBox[{"(", 
             FractionBox["1.25`", 
              SuperscriptBox["2", "n"]], ")"}], "2"], "-", "1"}], ")"}], " ", 
         
         RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
        SuperscriptBox[
         RowBox[{"(", 
          FractionBox["1.25`", 
           SuperscriptBox["2", "n"]], ")"}], "2"]}], ")"}]}]], "-", 
    FractionBox["0.01`", 
     FractionBox[
      SuperscriptBox["1.25`", "2"], 
      SuperscriptBox["2", "n"]]]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "\[Pi]"}], "}"}]}], "]"}]], "Output",
 CellChangeTimes->{3.397512353147572*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"n", " ", "=", " ", "1"}], "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.39751238641818*^9, 3.397512390328277*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{3.397512391701278*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData["n"], "Input",
 CellChangeTimes->{3.397512398369926*^9}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{3.397512399046776*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"FindRoot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1.25", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "/", "2"}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}], 
    " ", "-", " ", 
    RowBox[{"0.01", "*", 
     RowBox[{
      RowBox[{"1", "/", 
       RowBox[{"1.25", "^", "2"}]}], "/", 
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}]}]}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}]], "Input"],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "1.784684876476735`"}], "}"}]], "Output",
 CellChangeTimes->{3.397512409508109*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"n", " ", "=", " ", "7"}], "\[IndentingNewLine]", 
 RowBox[{"R", " ", "=", " ", 
  RowBox[{"FindRoot", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}],
      " ", "-", " ", 
     RowBox[{"0.1", "*", 
      RowBox[{
       RowBox[{"1", "/", 
        RowBox[{"1.25", "^", "2"}]}], "/", 
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}]}]}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}]}]}], "Input",
 CellChangeTimes->{{3.397512531289494*^9, 3.397512535902667*^9}, {
  3.397512607505209*^9, 3.397512710104786*^9}, {3.397512816093491*^9, 
  3.397512831709575*^9}, {3.397512906989706*^9, 3.397512969847936*^9}, {
  3.397513007930785*^9, 3.3975130118361*^9}, {3.397574925756058*^9, 
  3.397574934329342*^9}, {3.397574964935536*^9, 3.397574995593018*^9}, {
  3.397575065913237*^9, 3.397575082163777*^9}, {3.397575112911772*^9, 
  3.397575113324155*^9}}],

Cell[BoxData["7"], "Output",
 CellChangeTimes->{
  3.397512541008358*^9, {3.397512609441704*^9, 3.397512711461429*^9}, {
   3.397512823440108*^9, 3.397512832721762*^9}, {3.397512909354925*^9, 
   3.39751297077133*^9}, 3.397513014497781*^9, 3.397574942019699*^9, 
   3.397574998332696*^9, 3.397575084257457*^9, 3.397575118631024*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "0.02326704820962144`"}], "}"}]], "Output",
 CellChangeTimes->{
  3.397512541008358*^9, {3.397512609441704*^9, 3.397512711461429*^9}, {
   3.397512823440108*^9, 3.397512832721762*^9}, {3.397512909354925*^9, 
   3.39751297077133*^9}, 3.397513014497781*^9, 3.397574942019699*^9, 
   3.397574998332696*^9, 3.397575084257457*^9, 3.397575118784372*^9}]
}, Open  ]],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.397512603086577*^9, 3.397512604531302*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"0.02326704820962144", "*", 
   RowBox[{"180", "/", "Pi"}]}], "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.397512747826023*^9, 3.397512758118074*^9}, {
  3.397575041597138*^9, 3.397575051305479*^9}, {3.397575091505243*^9, 
  3.397575099390614*^9}, {3.397575130607009*^9, 3.397575138173677*^9}}],

Cell[BoxData["1.333103664138727`"], "Output",
 CellChangeTimes->{3.397512759892648*^9, 3.397575052546454*^9, 
  3.397575100390829*^9, 3.397575138620723*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData["x"], "Input",
 CellChangeTimes->{3.39751284649727*^9}],

Cell[BoxData["x"], "Output",
 CellChangeTimes->{3.397512848923769*^9}]
}, Open  ]],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.397512879357819*^9, 3.397512881148576*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"R", "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.397513024107202*^9, 3.397513029935665*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "0.017402970116360293`"}], "}"}]], "Output",
 CellChangeTimes->{3.397513032022914*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"n", " ", "=", " ", "2"}], "\[IndentingNewLine]", 
 RowBox[{"R", " ", "=", " ", 
  RowBox[{"FindRoot", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}],
      " ", "-", " ", 
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}], 
      " ", " "}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", "Pi"}], "}"}]}], "]"}]}]}], "Input",
 CellChangeTimes->{{3.397575432296202*^9, 3.397575492491246*^9}, {
  3.397575617537475*^9, 3.397575617643156*^9}}],

Cell[BoxData["2"], "Output",
 CellChangeTimes->{3.397575507361416*^9, 3.397575619074428*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "3.141592653589793`"}], "}"}]], "Output",
 CellChangeTimes->{3.397575507361416*^9, 3.397575619170353*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"n", " ", "=", " ", "8"}], "\[IndentingNewLine]", 
 RowBox[{"R", " ", "=", 
  RowBox[{"Plot", "[", 
   RowBox[{
    RowBox[{
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}],
      " ", "-", " ", 
     RowBox[{"2", "*", 
      RowBox[{
       RowBox[{"(", 
        RowBox[{"1", "/", 
         RowBox[{"2", "^", "n"}]}], ")"}], "/", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
           ")"}], "*", 
          RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
      RowBox[{"Exp", "[", 
       RowBox[{"-", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{"Tan", "[", 
            RowBox[{"x", "/", "2"}], "]"}], "/", 
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}], 
      " ", " "}]}], ",", 
    RowBox[{"{", 
     RowBox[{"x", ",", "0", ",", 
      RowBox[{"Pi", "/", "50"}]}], "}"}], ",", 
    RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]}]}], "Input",
 CellChangeTimes->{{3.397575640830101*^9, 3.397575641615314*^9}, {
  3.397579406443287*^9, 3.397579412350192*^9}, {3.397579777827984*^9, 
  3.397579824919171*^9}, {3.3975798772839*^9, 3.397579896813474*^9}}],

Cell[BoxData["8"], "Output",
 CellChangeTimes->{
  3.397575649585656*^9, 3.3975794132707*^9, {3.397579781699972*^9, 
   3.397579825559541*^9}, {3.397579880774694*^9, 3.397579897491715*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwUl3c8V/8Xx5FkJWQnmySEUCTnk+ysyEzIDiErIdlC2Xv72D72Svrcez9R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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  ImageMargins->{{0., 594.}, {10., 0.}},
  ImageSize->{807., Automatic},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.397575649585656*^9, 3.3975794132707*^9, {3.397579781699972*^9, 
   3.397579825559541*^9}, {3.397579880774694*^9, 3.397579897526747*^9}},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"n", " ", "=", " ", "8"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"R", "  ", "=", " ", 
   RowBox[{"FindRoot", "[", 
    RowBox[{
     RowBox[{
      RowBox[{
       RowBox[{"2", "*", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "/", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"(", 
                RowBox[{"1", "/", 
                 RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
             ")"}], "*", 
            RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
        RowBox[{"Exp", "[", 
         RowBox[{"-", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{"Tan", "[", 
              RowBox[{"x", "/", "2"}], "]"}], "/", 
             RowBox[{"(", 
              RowBox[{"1", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
         "]"}]}], " ", "-", " ", 
       RowBox[{"2", "*", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "/", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"(", 
                RowBox[{"1.25", "/", 
                 RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
             ")"}], "*", 
            RowBox[{"Cos", "[", "x", "]"}]}], "+", "1", "+", 
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
        RowBox[{"Exp", "[", 
         RowBox[{"-", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{"Tan", "[", 
              RowBox[{"x", "/", "2"}], "]"}], "/", 
             RowBox[{"(", 
              RowBox[{"1.25", "/", 
               RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
         "]"}]}]}], " ", "==", " ", 
      RowBox[{
       RowBox[{"-", "0.05"}], "*", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"2", "^", "n"}], " ", "-", " ", 
         RowBox[{
          RowBox[{"2", "^", "n"}], "/", 
          RowBox[{
           RowBox[{"(", "1.25", ")"}], "^", "2"}]}]}], ")"}]}]}], "  ", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0.015"}], "}"}]}], "]"}]}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", "*", 
           RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "*", 
            RowBox[{
             RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}], 
    " ", "-", " ", 
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", "*", 
           RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1.25", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "*", 
            RowBox[{
             RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
      "]"}]}]}], " ", " ", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "2"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.397580138648458*^9, 3.397580209503853*^9}, {
  3.397580345540298*^9, 3.397580410681568*^9}, {3.397580487977451*^9, 
  3.397580511518295*^9}, {3.397580543562372*^9, 3.397580578784229*^9}, {
  3.397580726347939*^9, 3.397580730185537*^9}, {3.397580796013178*^9, 
  3.397580803782668*^9}, {3.397580846166755*^9, 3.397580846848566*^9}, {
  3.397581986555874*^9, 3.397582019607142*^9}, {3.397582060247698*^9, 
  3.397582139819554*^9}, {3.397582232840316*^9, 3.397582233785841*^9}, {
  3.397583243283957*^9, 3.397583244892624*^9}}],

Cell[BoxData["8"], "Output",
 CellChangeTimes->{
  3.397580418309967*^9, {3.397580490583781*^9, 3.397580512633211*^9}, {
   3.397580545810327*^9, 3.397580579696287*^9}, 3.397580807241064*^9, 
   3.397580847764214*^9, 3.397582022107421*^9, {3.397582094382218*^9, 
   3.397582140395435*^9}, 3.39758223512376*^9, 3.397583247220753*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "0.013853411421573002`"}], "}"}]], "Output",
 CellChangeTimes->{
  3.397580418309967*^9, {3.397580490583781*^9, 3.397580512633211*^9}, {
   3.397580545810327*^9, 3.397580579696287*^9}, 3.397580807241064*^9, 
   3.397580847764214*^9, 3.397582022107421*^9, {3.397582094382218*^9, 
   3.397582140395435*^9}, 3.39758223512376*^9, 3.397583247262694*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwV13c8Ve8fAHCrzOxkc29Imd+QBj4nNGRkr8pKRYmyUgkpklFCkh0qhGRE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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.397580418309967*^9, {3.397580490583781*^9, 3.397580512633211*^9}, {
   3.397580545810327*^9, 3.397580579696287*^9}, 3.397580807241064*^9, 
   3.397580847764214*^9, 3.397582022107421*^9, {3.397582094382218*^9, 
   3.397582140395435*^9}, 3.39758223512376*^9, 3.397583247294288*^9},
 ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"0.013853411421573002", "*", 
   RowBox[{"180", "/", "Pi"}]}], "\[IndentingNewLine]"}]], "Input",
 CellChangeTimes->{{3.397582178854304*^9, 3.397582183713887*^9}, {
  3.397582255690639*^9, 3.397582257876892*^9}}],

Cell[BoxData["0.7937420063144631`"], "Output",
 CellChangeTimes->{3.397582185135337*^9, 3.397582258262585*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"n", " ", "=", " ", "9"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"R", "  ", "=", " ", 
   RowBox[{"FindRoot", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"2", "*", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"1", "/", 
          RowBox[{"2", "^", "n"}]}], ")"}], "/", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"(", 
               RowBox[{"1", "/", 
                RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
            ")"}], "*", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", "*", 
             RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{"1", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{"Tan", "[", 
             RowBox[{"x", "*", 
              RowBox[{
               RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
            RowBox[{"(", 
             RowBox[{"1", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
        "]"}]}], " ", "-", " ", 
      RowBox[{"2", "*", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"1", "/", 
          RowBox[{"2", "^", "n"}]}], ")"}], "/", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"(", 
               RowBox[{"1.25", "/", 
                RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], 
            ")"}], "*", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", "*", 
             RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
          RowBox[{
           RowBox[{"(", 
            RowBox[{"1.25", "/", 
             RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
       RowBox[{"Exp", "[", 
        RowBox[{"-", 
         RowBox[{
          RowBox[{"(", 
           RowBox[{
            RowBox[{"Tan", "[", 
             RowBox[{"x", "*", 
              RowBox[{
               RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
        "]"}]}]}], "   ", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "0.1"}], "}"}]}], "]"}]}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", "*", 
           RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "*", 
            RowBox[{
             RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], "]"}]}], 
    " ", "-", " ", 
    RowBox[{"2", "*", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{"1", "/", 
        RowBox[{"2", "^", "n"}]}], ")"}], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"(", 
             RowBox[{"1.25", "/", 
              RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}], "-", "1"}], ")"}],
          "*", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", "*", 
           RowBox[{"Pi", "/", "180"}]}], "]"}]}], "+", "1", "+", 
        RowBox[{
         RowBox[{"(", 
          RowBox[{"1.25", "/", 
           RowBox[{"2", "^", "n"}]}], ")"}], "^", "2"}]}], ")"}]}], "*", 
     RowBox[{"Exp", "[", 
      RowBox[{"-", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Tan", "[", 
           RowBox[{"x", "*", 
            RowBox[{
             RowBox[{"Pi", "/", "180"}], "/", "2"}]}], "]"}], "/", 
          RowBox[{"(", 
           RowBox[{"1.25", "/", 
            RowBox[{"2", "^", "n"}]}], ")"}]}], ")"}], "^", "2"}]}], 
      "]"}]}]}], " ", " ", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "1"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "All"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.397592583353867*^9, 3.397592620237938*^9}, {
   3.397592656300611*^9, 3.397592705823936*^9}, {3.397592914944143*^9, 
   3.397592916986239*^9}, {3.397592956547068*^9, 3.397593224191426*^9}, 
   3.397593325986024*^9}],

Cell[BoxData["9"], "Output",
 CellChangeTimes->{
  3.397592624040902*^9, 3.39759265723281*^9, {3.39759269777824*^9, 
   3.397592706977543*^9}, 3.397592917624073*^9, {3.397592963483305*^9, 
   3.397593224818409*^9}, 3.39759332688005*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"x", "\[Rule]", "0.19607519680385818`"}], "}"}]], "Output",
 CellChangeTimes->{
  3.397592624040902*^9, 3.39759265723281*^9, {3.39759269777824*^9, 
   3.397592706977543*^9}, 3.397592917624073*^9, {3.397592963483305*^9, 
   3.397593224818409*^9}, 3.39759332691453*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwV13c8Ve8fAHBERBFJZiiJyLiJEj7HKjNkhLjZ5FtWVkNGKKMhkoyIBrJF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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesOrigin->{0, 0},
  PlotRange->{All, All},
  PlotRangeClipping->True,
  PlotRangePadding->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.397592624040902*^9, 3.39759265723281*^9, {3.39759269777824*^9, 
   3.397592706977543*^9}, 3.397592917624073*^9, {3.397592963483305*^9, 
   3.397593224818409*^9}, 3.397593326940634*^9}]
}, Open  ]]
},
WindowSize->{1262, 1105},
WindowMargins->{{Automatic, 111}, {Automatic, 3}},
FrontEndVersion->"6.0 for Linux x86 (32-bit) (April 20, 2007)",
StyleDefinitions->"Default.nb"
]
(* End of Notebook Content *)

(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{}
*)
(*CellTagsIndex
CellTagsIndex->{}
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[590, 23, 1409, 42, 55, "Input"],
Cell[2002, 67, 682, 13, 57, "Message"],
Cell[2687, 82, 1086, 35, 73, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[3810, 122, 157, 3, 55, "Input"],
Cell[3970, 127, 98, 2, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[4105, 134, 1892, 49, 55, "Input"],
Cell[6000, 185, 62364, 1031, 903, 44231, 732, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[68401, 1221, 784, 22, 32, "Input"],
Cell[69188, 1245, 76157, 1258, 242, 63637, 1051, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[145382, 2508, 1361, 41, 55, "Input"],
Cell[146746, 2551, 973, 17, 75, "Message"],
Cell[147722, 2570, 1462, 41, 59, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[149221, 2616, 1746, 51, 77, "Input"],
Cell[150970, 2669, 45256, 752, 846, 29120, 485, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[196263, 3426, 1414, 45, 55, "Input"],
Cell[197680, 3473, 833, 15, 54, "Message"],
Cell[198516, 3490, 1191, 37, 63, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[199744, 3532, 1423, 46, 55, "Input"],
Cell[201170, 3580, 743, 13, 54, "Message"],
Cell[201916, 3595, 1186, 38, 89, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[203139, 3638, 160, 3, 55, "Input"],
Cell[203302, 3643, 70, 1, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[203409, 3649, 69, 1, 32, "Input"],
Cell[203481, 3652, 70, 1, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[203588, 3658, 1299, 43, 55, "Input"],
Cell[204890, 3703, 138, 3, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[205065, 3711, 1886, 52, 55, "Input"],
Cell[206954, 3765, 332, 5, 31, "Output"],
Cell[207289, 3772, 402, 7, 31, "Output"]
}, Open  ]],
Cell[207706, 3782, 92, 1, 32, "Input"],
Cell[CellGroupData[{
Cell[207823, 3787, 340, 6, 55, "Input"],
Cell[208166, 3795, 156, 2, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[208359, 3802, 68, 1, 32, "Input"],
Cell[208430, 3805, 70, 1, 31, "Output"]
}, Open  ]],
Cell[208515, 3809, 92, 1, 32, "Input"],
Cell[CellGroupData[{
Cell[208632, 3814, 128, 2, 55, "Input"],
Cell[208763, 3818, 141, 3, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[208941, 3826, 2308, 71, 77, "Input"],
Cell[211252, 3899, 92, 1, 31, "Output"],
Cell[211347, 3902, 160, 3, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[211544, 3910, 2471, 74, 77, "Input"],
Cell[214018, 3986, 189, 3, 31, "Output"],
Cell[214210, 3991, 31029, 516, 524, 22412, 373, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[245276, 4512, 5565, 165, 187, "Input"],
Cell[250844, 4679, 332, 5, 31, "Output"],
Cell[251179, 4686, 403, 7, 31, "Output"],
Cell[251585, 4695, 19058, 319, 232, 13799, 231, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[270680, 5019, 246, 5, 55, "Input"],
Cell[270929, 5026, 110, 1, 31, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[271076, 5032, 5166, 159, 165, "Input"],
Cell[276245, 5193, 236, 4, 31, "Output"],
Cell[276484, 5199, 306, 6, 31, "Output"],
Cell[276793, 5207, 14020, 235, 229, "Output"]
}, Open  ]]
}
]
*)

(* End of internal cache information *)
